Big data is changing the world. Offered through the Department of Mathematics, this degree prepares you to take part in the data revolution. Students earning a Bachelor of Science or Bachelor of Arts in Statistics and Data Science will have a solid foundation in mathematics. Yet they focus on the capture, maintenance, processing, analysis and communication of data through immersion in courses in probability, statistics, data science and computer programming. Undergraduates also must complete a minor outside the Department of Mathematics. The B.A. and B.S. allow students to pursue graduate degrees or careers in analytics, risk assessment, finance, and other math- and science-related fields.
Business Information Systems, Data Science& Big Data& Data analysis, Natural Sciences & Mathematics, Statistics
4 years | Full time
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The Statistics & Data Science Interdisciplinary Program offers interdisciplinary courses of study leading to the Master of Science (M.S.) and Doctor of Philosophy (Ph.D.) degrees in Statistics (regular track or statistical informatics track), along with a 12-unit Graduate Certificate. A Ph.D. minor in Statistics is also available for students already registered into a Ph.D. program other than Statistics here at the UA. Our mission is to develop the next generation of data scientists, trained to meet the challenges of modern interdisciplinary data extraction, analysis, and interpretation.
The GIDP supports and encourages the central role of statistical and quantitative thinking in the biological, physical, engineering, financial, and social sciences. Necessary training is provided for students to develop core expertise in statistical theory and methodology, and also for students who will apply their statistical knowledge in practical, transdisciplinary research; targeted subject-matter specialties include, but are not limited to biometry, bioinformatics, biostatistics, econometrics & financial statistics, educational statistics, operations research & applied probability, psychometrics, spatial/spatio-temporal analysis, statistical genetics/genomics, stochastic modeling, and quantitative risk assessment.
Only one is required